Building blood based DNA methylation signatures for AD that are reflective of CNS changes Project Summary Alzheimer's disease (AD) is the most common neurodegenerative disorder, affecting about 6% of people 65 years and older worldwide. Currently only symptomatic treatments are available for AD, neuroprotective treatment to stop or even slow neurodegeneration remains elusive. A major challenge in clinical trials for AD is that in addition to disease modifying action, neuroprotective agents may also have symptomatic effects unrelated to the underlying disease. Typically, clinical trials uses measures of cognition as endpoints to assess treatments for AD. However, clinical endpoints cannot separate symptomatic effects of potential therapeutic agents from true disease-modifying effects. In this study we will develop blood based DNA methylation biomarkers for measuring disease progression in AD. A major challenge is that biomarkers detected in blood alone might not reflect central nervous system changes. To address this challenge, we will develop two innovative approaches for identifying blood based biomarkers predicative of AD progression by leveraging information from a dataset with matched brain and blood methylation samples, so that the biomarkers we identified in the periphery are also reflective of central nervous system changes. In Aim 1, we will identify methylated regions associated with AD progression in both brain and blood datasets, by testing one genomic region at a time. In Aim 2, we will assess prediction accuracy of multiple genomic regions to identify methylation signatures with relevant changes in brain for AD progression. In Aim 3, we will implement the analytical tools in an open source, user-friendly software and share the methylation data analysis results in a web interface. The identification of DNA methylation signatures for AD progression in peripheral blood of subjects would help facilitate the development of surrogate biomarkers for AD clinical trials by providing a degree of objectivity and detection of pathological progression without relying on symptoms, which will reduce both duration and the number of patients needed for AD clinical trials. In addition, an accurate biomarker of AD progression would also have the potential for diagnosing AD early in its course and would be invaluable for initiating early intervention and individualized treatment plan.